[HTML][HTML] Hybrid approaches to optimization and machine learning methods: a systematic literature review
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
[HTML][HTML] Machine learning-based boosted regression ensemble combined with hyperparameter tuning for optimal adaptive learning
Over the past couple of decades, many telecommunication industries have passed through
the different facets of the digital revolution by integrating artificial intelligence (AI) techniques …
the different facets of the digital revolution by integrating artificial intelligence (AI) techniques …
[HTML][HTML] Rolling bearing fault diagnosis based on WGWOA-VMD-SVM
J Zhou, M Xiao, Y Niu, G Ji - Sensors, 2022 - mdpi.com
A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-
variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was …
variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was …
Machine learning assisted probabilistic creep-fatigue damage assessment
In order to investigate the probabilistic damage distribution under creep-fatigue interaction,
machine learning framework with the divide-and-conquer methodology is proposed to …
machine learning framework with the divide-and-conquer methodology is proposed to …
Mobile botnet detection: a comprehensive survey
The number of people using mobile devices is increasing as mobile devices offer different
features and services. Many mobile users install various applications on their mobile …
features and services. Many mobile users install various applications on their mobile …
Cyber threat prediction using dynamic heterogeneous graph learning
Predicting cyber threats is crucial for uncovering underlying security risks and proactively
preventing malicious attacks. However, predicting cyber threats and demystifying the …
preventing malicious attacks. However, predicting cyber threats and demystifying the …
Failure analysis and control of natural gas pipelines under excavation impact based on machine learning scheme
D Xu, L Chen, C Yu, S Zhang, X Zhao, X Lai - International Journal of …, 2023 - Elsevier
Third-party excavation operations pose a serious threat to the safe operation of natural gas
pipelines, and quantifying the failure conditions of pipelines can effectively identify the …
pipelines, and quantifying the failure conditions of pipelines can effectively identify the …
Applications of artificial intelligence to detect android botnets: a survey
AM Almuhaideb, DY Alynanbaawi - IEEE Access, 2022 - ieeexplore.ieee.org
From the growing popularity of Android smart devices, and especially with the recent
advances brought on by the COVID-19 pandemic on digital adoption and transformation, the …
advances brought on by the COVID-19 pandemic on digital adoption and transformation, the …
Grey wolf optimization based support vector machine model for tool wear recognition in fir-tree slot broaching of aircraft turbine discs
S Ying, Y Sun, C Fu, L Lin, S Zhang - Journal of Mechanical Science and …, 2022 - Springer
Broaching tool condition monitoring is the basis of intelligent manufacturing of high-end
broaching equipment. There are still technical bottlenecks in tool wear recognition accuracy …
broaching equipment. There are still technical bottlenecks in tool wear recognition accuracy …
A framework based on heterogeneous ensemble models for liquid steel temperature prediction in LF refining process
C Chen, N Wang, M Chen, X Yan - Applied Soft Computing, 2022 - Elsevier
The precise control of liquid steel temperature in the ladle furnace (LF) refining process is
vital for stabilizing and improving the quality of liquid steel, necessitating a capable …
vital for stabilizing and improving the quality of liquid steel, necessitating a capable …